164 citations · 535 across the 44 of their papers we have counts for
3 papers · 1 filter
LSTM Acoustic Models Learn to Align and Pronounce with Graphemes
Arindrima Datta, Guanlong Zhao, Bhuvana Ramabhadran +1
Automated speech recognition coverage of the world's languages continues to expand. However, standard phoneme based systems require handcrafted lexicons that are difficult and expe…
Language-agnostic Multilingual Modeling
Arindrima Datta, Bhuvana Ramabhadran, Jesse Emond +2
Multilingual Automated Speech Recognition (ASR) systems allow for the joint training of data-rich and data-scarce languages in a single model. This enables data and parameter shari…
Generating diverse and natural text-to-speech samples using a quantized fine-grained VAE and auto-regressive prosody prior
Guangzhi Sun, Yu Zhang, Ron J. Weiss +5
Recent neural text-to-speech (TTS) models with fine-grained latent features enable precise control of the prosody of synthesized speech. Such models typically incorporate a fine-gr…